With an unprecedented amount of available text, our problem is not needing to write more of it; instead, we must learn to negotiate the vast quantity that exists. How I make my way through this thicket of information—how I manage it, parse it, organize and distribute it—is what distinguishes my writing from yours.

The prominent literary critic Marjorie Perloff has recently begun using the term “unoriginal genius” to describe this tendency emerging in literature. Her idea is that, because of changes brought on by technology and the Internet, our notion of the genius—a romantic, isolated figure—is outdated. An updated notion of genius would have to center around one’s mastery of information and its dissemination. Perloff has coined another term, “moving information,” to signify both the act of pushing language around as well as the act of being emotionally moved by that process. She posits that today’s writer resembles more a programmer than a tortured genius, brilliantly conceptualizing, constructing, executing, and maintaining a writing machine.

In the fall of 1960, during his second year of graduate school, Ted Nelson found out about computers, and not a moment too soon. He was drowning in his own information, carrying around an already monumental collection of barely collated notes about his abundant dreams and schemes. He found out about Vannevar Bush’s paper and embraced the idea that he could use a computer to keep track of his own prodigious stream of thoughts and sketches.

Ted was disappointed to discover that there were no computers equipped or programmed to perform such a service. Down the road at MIT, the first time-sharing computers were only beginning to be built. But Ted needed a storage and retrieval system to keep track of his notes, and it seemed like such an obvious way to use computers as aids to creative thought that he set out to create such a program himself. Twenty-three years later, he admitted: “It seemed so simple and clear to me then. It still does. But like so many beginning computerists, I mistook a clear view for a short distance. “

The Harvard course in computer programming that Ted took in 1960 used the only computer then available at Harvard, the IBM 7090 at the Smithsonian Observatory. As a term project, Ted decided to write a machine-language program that would enable him to store his notes and manuscripts in the computer, to change and edit drafts in various ways, and produce final printed versions. Somewhere around the forty-thousandth line of his program, it dawned on him that his first estimates of the magnitude of the task — and the amount of time it would take to establish it — had been overoptimistic.

Nelson’s inability to create something even though he was able to clearly envision it is not unusual in the software world. The problem is so widespread that one of the unofficial rules of computer programming (known in some circles as “Babbage’s Law”) is: “Any large programming project will always take twice as long as you estimate.” Even though the simplest of the text-handling capabilities he specified in 1960 were to become, in the hands of other programmers, the software spearhead of office automation in the 1980s, Nelson went far beyond simple text manipulation in the program he set out to write for his term project.

Like Doug Engelbart, whose work he had yet to learn about, Nelson yearned for more than a lazy man’s typewriter. They both wanted the freedom to steer their thought paths in new ways. And Ted especially desired the prerogative of changing his mind. He wanted the freedom to insert and delete words and move paragraphs around, but he also wanted the computer to remember his decision path. One of the specs was for something he called “historical backtrack,” in which the computer could quickly show him the various earlier alternative versions of his ever-changing text.

“Alternative versions”? From a place to store notes to a tool for sculpting text, his term project had now landed him in even more wondrous science-fiction territory, a place where it was possible to think in terms of parallel alternatives. Of entire libraries of parallel alternatives, and automated librarians to perform the most tedious of searches in microseconds. Why should we abandon any thought at all? Why not just store every variation on everything and let the computer take care of sifting through it when we want to view something?

Yet psychologically, we all — all of us – have this dramatically different response to a senseless death when it is an 8-year-old in Boston, vs. when it’s an 8-year-old in Fallujah. That flies in the face of almost all of our ethical worldviews, yet it is an inescapable psychological phenomenon.

It’s like, we all know that this thing is wrong — this vacillation between caring and uncaring on the basis of arbitrary things like distance and nationality — yet we all do it anyway.

It’s Wednesday at 12:30 in downtown Manhattan. Good starting point; we know New York like the back of our hands. The user (let’s call him Connor) has 78 friends on Foursquare, and out of those friends, let’s say 40 of them have spent some time in New York City, some more than others.

Alright, looking good so far — now what do we do with this? We start to look at places that Connor has told us he likes, looking back at previous check-ins and places he has rated on Foursquare. Now we look to Connor’s social graph of those 40 friends, and we see what places align with his tastes. For instance, he may be big on ramen, and so may a few of his friends, so now it’s time for some behind-the-scenes math. We begin to align what ramen restaurants resonate well with his social graph and also have a good rating. The ratings can vary dramatically from how popular it is to a slew of other variables.

Keep in mind that all of this is being served up without an explicit search for “ramen.” We just know enough about Connor to make a informed suggestion and then continue to monitor his behavior and improve these recommendations for him as he and his friend graph continue to grow. Connor has been to Momofuku, but he’s very close to Ippudo, which a couple of his friends have been to, and three even rated very highly. I think we have a winner.

Want to make people run? Don’t give them a badge for running. Give them a ball and shove four sticks in the ground. They’ll run around the field chasing the ball (and each other) for ages. The experience is intrinsically challenging and amusing, and the running is a by-product. Games rely on dynamics like these and rules to generate the conditions for positive engagement.

…The badges in and of themselves are meaningless. They’re only of value in the context of an activity that is intrinsically rewarding enough to make people want to participate in it. When an activity is designed well enough to be intrinsically rewarding, you can start assigning extra rewards like badges. These rewards gain endogenous value – a value that truly exists only within the context of the game.